---
title: "Who cites Ling Feng — 56 papers of our library"
description: "56 papers of the Elamur Research library cite the works of Ling Feng, found in their bibliographies; the most cited first."
canonical: "https://research.elamur.ai/free/en/authors/ling-feng/cited-by/"
---
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# Who cites Ling Feng

56 citations of their works from 56 papers of our library (of the 149,439 whose bibliographies we read) · 26 with a page here, the most cited first · [← Ling Feng](https://md.research.elamur.ai/free/en/authors/ling-feng/)

1. [**Stop Overthinking: A Survey on Efficient Reasoning for Large Language Models arXiv:2503.16419**Yang Sui, Yu-Neng Chuang, Guanchu Wang, et al.*2025 · 157 citations*](https://md.research.elamur.ai/free/en/papers/sui-2025-stop-overthinking-survey-efficient-reasoning/)
2. [**Dynamic Early Exit in Reasoning Models arXiv:2504.15895**Chenxu Yang, Qingyi Si, Yongjie Duan, et al.*2025 · 74 citations*](https://md.research.elamur.ai/free/en/papers/yang-2025-dynamic-early-exit-reasoning-models/)
3. [**InftyThink: Breaking the Length Limits of Long-Context Reasoning in Large Language Models arXiv:2503.06692**Yuchen Yan, Yongliang Shen, Yang Liu, et al.*2025 · 29 citations*](https://md.research.elamur.ai/free/en/papers/yan-2025-inftythink-breaking-length-limits-long/)
4. **[Transforming Science with Large Language Models: A Survey on AI-assisted Scientific Discovery, Experimentation, Content Generation, and Evaluation](https://md.research.elamur.ai/free/en/papers/eger-2025-transforming-science-large-language-models/) [ACM Computing Surveys](https://md.research.elamur.ai/free/en/venues/acm-computing-surveys/)**Steffen Eger, Yong Cao, Jennifer D'Souza, et al.*2025 · 25 citations*
5. **[AttnPO: Attention-Guided Process Supervision for Efficient Reasoning](https://md.research.elamur.ai/free/en/papers/nie-2026-attnpo-attention-guided-process-supervision/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Shuaiyi Nie, Dingsiyu, Wenyuan Zhang, et al.*2026 · 18 citations*
6. **[NeuReasoner: Towards Explainable, Controllable, and Unified Reasoning via Mixture-of-Neurons](https://md.research.elamur.ai/free/en/papers/dong-2026-neureasoner-explainable-controllable-unified-reasoning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Haonan Dong, Kehan Jiang, Haoran Ye, et al.*2026 · 13 citations*
7. [**Pangu Embedded: An Efficient Dual-system LLM Reasoner with Metacognition arXiv:2505.22375**Hanting Chen, Yasheng Wang, Kai Han, et al.*2025 · 13 citations*](https://md.research.elamur.ai/free/en/papers/chen-2025-pangu-embedded-efficient-dual/)
8. **[Step Potential Advantage Estimation: Harnessing Intermediate Confidence and Correctness for Efficient Mathematical Reasoning](https://md.research.elamur.ai/free/en/papers/wu-2026-step-potential-advantage-estimation-harnessing/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Fei Wu, Zhenrong Zhang, Qikai Chang, et al.*2026 · 11 citations*
9. **[Reason Only When Needed: Efficient Generative Reward Modeling via Model-Internal Uncertainty](https://md.research.elamur.ai/free/en/papers/xue-2026-reason-only-when-needed-efficient/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Chao Xue, Yao Wang, Mengqiao Liu, et al.*2026 · 8 citations*
10. **[Revisiting Model Interpolation for Efficient Reasoning](https://md.research.elamur.ai/free/en/papers/wu-2026-revisiting-model-interpolation-efficient-reasoning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Taiqiang Wu, Runming Yang, Tao Liu, et al.*2026 · 6 citations*
11. **[DeepPrune: Parallel Scaling without Inter-trace Redundancy](https://md.research.elamur.ai/free/en/papers/tu-2026-deepprune-parallel-scaling-without-inter/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Shangqing Tu, Yaxuan Li, Yushi Bai, et al.*2026 · 3 citations*
12. **[OpenGenAlign: A Preference Dataset and Benchmark for Trustworthy Reward Modeling in Open-Ended, Long-Context Generation](https://md.research.elamur.ai/free/en/papers/zhang-2026-opengenalign-preference-dataset-benchmark-trustworthy/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Hanning Zhang, Juntong Song, Juno Zhu, et al.*2026 · 2 citations*
13. **[Reinforced Informativeness Optimization for Long-Form Retrieval-Augmented Generation](https://md.research.elamur.ai/free/en/papers/wang-2026-reinforced-informativeness-optimization-long-form/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yuhao Wang, Ruiyang Ren, Yucheng Wang, et al.*2026 · 2 citations*
14. **[Think How to Think: Mitigating Overthinking with Autonomous Difficulty Cognition in Large Reasoning Models](https://md.research.elamur.ai/free/en/papers/liu-2026-think-how-think-mitigating-overthinking/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yongjiang Liu, Haoxi Li, Xiaosong Ma, et al.*2026 · 2 citations*
15. **[Anti-Length Shift: Dynamic Outlier Truncation for Training Efficient Reasoning Models](https://md.research.elamur.ai/free/en/papers/wu-2026-anti-length-shift-dynamic-outlier/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Wei Wu, Liyi Chen, Congxi Xiao, et al.*2026 · 1 citation*
16. **[Correct, Concise and Complete: Multi-stage Training For Adaptive Reasoning](https://md.research.elamur.ai/free/en/papers/rakotonirina-2026-correct-concise-complete-multi-stage/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Nathanaël Carraz Rakotonirina, Ren Pang, Neha Anna John, et al.*2026 · 1 citation*
17. **[From Interpretability to Performance: Optimizing Retrieval Heads for Long-Context Language Models](https://md.research.elamur.ai/free/en/papers/ma-2026-interpretability-performance-optimizing-retrieval-heads/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Youmi Ma, Naoaki Okazaki*2026 · 1 citation*
18. **[NEAT: Neuron-Based Early Exit for Large Reasoning Models](https://md.research.elamur.ai/free/en/papers/liu-2026-neat-neuron-based-early-exit/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Kang Liu, YongKang Liu, Xiaocui Yang, et al.*2026 · 1 citation*
19. **[Aligning Agents via Planning: A Benchmark for Trajectory-Level Reward Modeling](https://md.research.elamur.ai/free/en/papers/wang-2026-aligning-agents-planning-benchmark-trajectory/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jiaxuan Wang, Yulan Hu, Wenjin Yang, et al.*2026*
20. **[ARM2: Adaptive Reasoning Model with Vision Understanding and Executable Code](https://md.research.elamur.ai/free/en/papers/xie-2026-arm2-adaptive-reasoning-model-vision/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jian Xie, Zhendong Chu, Aoxiao Zhong, et al.*2026*
21. **[Beyond Simple Term Injection: Reasoning Models for Legal Translation in a Non-Dominant Language Variety](https://md.research.elamur.ai/free/en/papers/natale-2026-beyond-simple-term-injection-reasoning/) [Annual Conference of the European Association for Machine Translation (EAMT)](https://md.research.elamur.ai/free/en/venues/eamt/)**Paolo Di Natale, Elena Chiocchetti, Marlies Alber, et al.*2026*
22. **[Data Foundations of Long-Context Language Models: A Survey](https://md.research.elamur.ai/free/en/papers/sun-2026-data-foundations-long-context-language/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Zechen Sun, Yuyang Sun, Zhaochen Su, et al.*2026*
23. **[Exploration-Exploitation Reshaping towards Efficient Reasoning for Large Language Models](https://md.research.elamur.ai/free/en/papers/shi-2026-exploration-exploitation-reshaping-efficient-reasoning/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yufeng Shi, Weilin Luo, Yuxiang Zhang, et al.*2026*
24. **[Merlin's Whisper: Enabling Efficient Reasoning in Large Language Models via Black-box Persuasive Prompting](https://md.research.elamur.ai/free/en/papers/xia-2026-merlin-s-whisper-enabling-efficient/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Heming Xia, Cunxiao Du, Rui Li, et al.*2026*
25. **[Think Less, Know More: State-Aware Reasoning Compression with Knowledge Guidance for Efficient Reasoning](https://md.research.elamur.ai/free/en/papers/sui-2026-think-less-know-more-state/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yi Sui, Chaozhuo Li, Dawei Song*2026*
26. **[WildReward: Learning Reward Models from In-the-Wild Human Interactions](https://md.research.elamur.ai/free/en/papers/peng-2026-wildreward-learning-reward-models-wild/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Hao Peng, Yunjia Qi, Xiaozhi Wang, et al.*2026*

30 more citing papers of our library have no page here yet.

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